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  <meta name="description" content="前言在上篇，我们获得了豆瓣二百五的电影URL，然后存储在了一个文件里。接下来，我们要访问每一个电影URL，深入敌后，获取情报~ 所有的代码都已存储在我的Github仓库：Douban_250当中~ 设置爬取规则对于每一个电影，我们选择爬取如下内容（虽然电影列表页就能爬得到= =）： 12标题（title）、年份（year）、时长（time）、导演（director）、类型（genre）、评分（sc">
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<meta property="og:description" content="前言在上篇，我们获得了豆瓣二百五的电影URL，然后存储在了一个文件里。接下来，我们要访问每一个电影URL，深入敌后，获取情报~ 所有的代码都已存储在我的Github仓库：Douban_250当中~ 设置爬取规则对于每一个电影，我们选择爬取如下内容（虽然电影列表页就能爬得到= =）： 12标题（title）、年份（year）、时长（time）、导演（director）、类型（genre）、评分（sc">
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<meta name="twitter:description" content="前言在上篇，我们获得了豆瓣二百五的电影URL，然后存储在了一个文件里。接下来，我们要访问每一个电影URL，深入敌后，获取情报~ 所有的代码都已存储在我的Github仓库：Douban_250当中~ 设置爬取规则对于每一个电影，我们选择爬取如下内容（虽然电影列表页就能爬得到= =）： 12标题（title）、年份（year）、时长（time）、导演（director）、类型（genre）、评分（sc">






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          <h2 class="post-title" itemprop="name headline">【Easy Python】第四话：爬虫初探——玩转豆瓣二百五（下）

              
            
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        <h2 id="前言"><a href="#前言" class="headerlink" title="前言"></a>前言</h2><p>在上篇，我们获得了豆瓣二百五的电影URL，然后存储在了一个文件里。接下来，我们要访问每一个电影URL，深入敌后，获取情报~</p>
<p>所有的代码都已存储在我的Github仓库：<span class="exturl" data-url="aHR0cHM6Ly9naXRodWIuY29tL3V0bWhpa2FyaS9Eb3ViYW5fMjUw" title="https://github.com/utmhikari/Douban_250">Douban_250<i class="fa fa-external-link"></i></span>当中~</p>
<h2 id="设置爬取规则"><a href="#设置爬取规则" class="headerlink" title="设置爬取规则"></a>设置爬取规则</h2><p>对于每一个电影，我们选择爬取如下内容（虽然电影列表页就能爬得到= =）：</p>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">标题（title）、年份（year）、时长（time）、</span><br><span class="line">导演（director）、类型（genre）、评分（score）</span><br></pre></td></tr></table></figure>
<p>随意点击一个电影页面，用上篇所说的提取CSS选择器的方法，我们可以制作出每一种内容与内容提取规则的映射。如下所示：</p>
<a id="more"></a>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># sp就是上篇所说的soup解析器</span></span><br><span class="line"><span class="comment"># 每一种内容都可以在解析器中按特定的规则提取加工得到</span></span><br><span class="line">content_func_map = &#123;</span><br><span class="line">    <span class="string">'title'</span>: <span class="keyword">lambda</span> sp: sp.select_one(<span class="string">'#content &gt; h1 &gt; span:nth-child(1)'</span>).get_text(),</span><br><span class="line">    <span class="string">'year'</span>: <span class="keyword">lambda</span> sp: sp.select_one(<span class="string">'#content &gt; h1 &gt; span.year'</span>).get_text().replace(<span class="string">'('</span>, <span class="string">''</span>).replace(<span class="string">')'</span>, <span class="string">''</span>),</span><br><span class="line">    <span class="string">'time'</span>: <span class="keyword">lambda</span> sp: sp.select_one(<span class="string">'#info &gt; span[property="v:runtime"]'</span>).get_text(),</span><br><span class="line">    <span class="string">'director'</span>: <span class="keyword">lambda</span> sp: sp.select_one(<span class="string">'#info &gt; span:nth-child(1) &gt; span.attrs &gt; a'</span>).get_text(),</span><br><span class="line">    <span class="string">'genre'</span>: <span class="keyword">lambda</span> sp: list(map(<span class="keyword">lambda</span> item: item.get_text(), sp.select(<span class="string">'#info &gt; span[property="v:genre"]'</span>))),</span><br><span class="line">    <span class="string">'score'</span>: <span class="keyword">lambda</span> sp: sp.select_one(<span class="string">'#interest_sectl &gt; div.rating_wrap.clearbox &gt; div.rating_self.clearfix &gt; strong'</span>).get_text()</span><br><span class="line">&#125;</span><br></pre></td></tr></table></figure>
<p>设置完规则，大问题来了= =250个链接，一个个访问，应该会很慢吧！而且，豆瓣还有反爬虫机制，如果访问间隔太快，就会暂时封ip——这，这可怎么办呀！</p>
<h2 id="人海战术，代理爬虫"><a href="#人海战术，代理爬虫" class="headerlink" title="人海战术，代理爬虫"></a>人海战术，代理爬虫</h2><p>一个个访问慢的话，一起访问，似乎会更快的吧= =<br>豆瓣封ip的话，如果有多个ip，效率也会增加的吧= =</p>
<h3 id="效率调度"><a href="#效率调度" class="headerlink" title="效率调度"></a>效率调度</h3><p>理想状态下，我们希望爬取每一个url的过程，都能够被当作是一个任务（task）。就像在M记一样，前台每收到一个客人的订单，都会把订单任务直接扔给厨师们，然后处理下一个客人的请求。那么，我们的厨师在哪里？</p>
<p>得益于python内置的<code>asyncio</code>库，我们可以模拟厨师们的工作，调度每一个爬虫任务。</p>
<p>然而，即使有了<code>asyncio</code>库，我们也只是通过其中的调度机制，重构了CPU指令而已，对于某些阻塞（block）任务进度的过程，并不能妥善解决。在爬取url内容的过程中，最阻碍我们任务进度的，当属请求——响应的阶段。对于调度器来讲，一个任务发送请求出去，调度器并不需要让它傻等响应回来，而是可以让这个任务歇一下，把执行权让（yield）给其它任务，直到响应回来后，再通知这个任务继续原来的工作，这样才够效率。上一章我们用的<code>requests</code>库不支持这一种机制，没关系，我们可以利用第三方的<code>aiohttp</code>库，完成这个需求。</p>
<h3 id="获取代理池"><a href="#获取代理池" class="headerlink" title="获取代理池"></a>获取代理池</h3><p>HTTP请求支持我们通过代理发送数据，使得目标识别发送源为代理服务器。要短时间获取大量的代理服务器地址，很简单，随便找个比如<span class="exturl" data-url="aHR0cHM6Ly93d3cueGljaWRhaWxpLmNvbS8=" title="https://www.xicidaili.com/">西刺代理<i class="fa fa-external-link"></i></span>或者<span class="exturl" data-url="aHR0cDovL3d3dy42NmlwLmNuL3B0Lmh0bWw=" title="http://www.66ip.cn/pt.html">66代理<i class="fa fa-external-link"></i></span>，利用内置查询，或者HTML解析爬取一堆，搞个一两千个就好。</p>
<h3 id="代理服务器分配"><a href="#代理服务器分配" class="headerlink" title="代理服务器分配"></a>代理服务器分配</h3><p>在我们的人海战术里，每一个爬虫任务开始前，都需要分配到一个代理服务器。所以问题来了——代理服务器，该怎么分配给每一个任务呢？我们希望，每一个任务都像被等待点名一样，如果有可用的代理服务器就挑几个任务去用，如果暂时能用的代理服务器都在用的话，就歇一会儿。</p>
<p>当然，如果没有代理服务器能用，就凉凉了= =</p>
<p>得益于<code>asyncio</code>库提供条件变量（Condition Variable）的机制，可以满足我们的需求。需要获得资源的任务，就去等待（wait）资源分配器的通知，资源分配器发现资源可用，则去通知（notify）那些迫不及待的任务，叫他们赶紧获取资源去。具体如何操作？且让我徐徐道来~</p>
<p>首先，在爬虫任务开始之前，我们得把“获取代理池”一步拿到的代理服务器列表，放到咱们内存里。</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br></pre></td><td class="code"><pre><span class="line"> <span class="comment"># 初始化条件变量</span></span><br><span class="line">cond = <span class="literal">None</span></span><br><span class="line"><span class="comment"># 代理队列采用deque()数据结构，头尾都可以添加/删除，便于代理重复利用</span></span><br><span class="line">proxies = deque()</span><br><span class="line"><span class="comment"># 存放当前正在使用的代理，如果同时被多个任务用的话，小心被豆瓣封= =</span></span><br><span class="line">proxies_used = set()</span><br><span class="line"></span><br><span class="line"></span><br><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">get_proxies</span><span class="params">()</span>:</span></span><br><span class="line">    <span class="string">"""</span></span><br><span class="line"><span class="string">    获取存好的代理服务器列表</span></span><br><span class="line"><span class="string">    """</span></span><br><span class="line">    contents = open(<span class="string">'proxies.txt'</span>, encoding=<span class="string">'utf-8'</span>).read().splitlines()</span><br><span class="line">    <span class="keyword">for</span> i <span class="keyword">in</span> range(len(contents)):</span><br><span class="line">        <span class="keyword">if</span> <span class="keyword">not</span> contents[i].startswith(<span class="string">'http'</span>):</span><br><span class="line">            contents[i] = <span class="string">'http://'</span> + contents[i]</span><br><span class="line">    proxies.extend(set(contents))</span><br></pre></td></tr></table></figure>
<p>然后，开始添加我们的任务啦</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># 创建用于发送HTTP请求的客户端</span></span><br><span class="line"><span class="keyword">async</span> <span class="keyword">with</span> aiohttp.ClientSession() <span class="keyword">as</span> session:</span><br><span class="line">    <span class="comment"># 电影数量</span></span><br><span class="line">    num_urls = len(movie_urls)</span><br><span class="line">    <span class="comment"># 初始化条件变量Condition Variable</span></span><br><span class="line">    <span class="keyword">global</span> cond</span><br><span class="line">    cond = asyncio.Condition()</span><br><span class="line">    <span class="comment"># 添加任务啦~</span></span><br><span class="line">    tasks = list()</span><br><span class="line">    <span class="keyword">for</span> i <span class="keyword">in</span> range(num_urls):</span><br><span class="line">        <span class="comment"># crawl_movie_url就是我们爬虫任务的模版啦，具体见下面</span></span><br><span class="line">        tasks.append(crawl_movie_url(session, movie_urls[i], i + <span class="number">1</span>))</span><br><span class="line">    <span class="comment"># 最后一个启动的任务是咱们的代理分配模块：allocate_proxy</span></span><br><span class="line">    tasks.append(allocate_proxy(len(tasks)))</span><br><span class="line">    <span class="comment"># 开始把这堆任务跑起来，走你~</span></span><br><span class="line">    <span class="keyword">await</span> asyncio.gather(*tasks)</span><br></pre></td></tr></table></figure>
<p>对于每一个任务，我们都做成一个循环（loop），直到任务完成或者没有代理服务器可用，才退出不干。因此，爬虫任务的初始逻辑如下：</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># 加了async，表示这个函数上升为一个可被asyncio模块调度的任务</span></span><br><span class="line"><span class="keyword">async</span> <span class="function"><span class="keyword">def</span> <span class="title">crawl_movie_url</span><span class="params">(session, url, movie_num)</span>:</span></span><br><span class="line">    <span class="keyword">while</span> <span class="literal">True</span>:</span><br><span class="line">        <span class="comment"># 加了await，该任务就歇了，保存该任务状态，CPU执行权交给其它任务</span></span><br><span class="line">        <span class="comment"># 直到get_proxy有结果才被asyncio调度器唤醒</span></span><br><span class="line">        proxy = <span class="keyword">await</span> get_proxy()</span><br><span class="line">        <span class="keyword">if</span> <span class="keyword">not</span> proxy:</span><br><span class="line">            log(movie_num, <span class="string">'TMD代理全部挂了，凉凉= ='</span>)</span><br><span class="line">            <span class="keyword">return</span></span><br><span class="line">        <span class="comment"># 开始执行爬虫任务啦，具体后面说= =</span></span><br><span class="line">        <span class="keyword">await</span> set_proxy_in_use(proxy)</span><br><span class="line">        <span class="keyword">pass</span></span><br></pre></td></tr></table></figure>
<p>对于每一个任务来讲，该如何获取代理服务器呢？咱们的<code>get_proxy</code>任务代码如下：</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">async</span> <span class="function"><span class="keyword">def</span> <span class="title">get_proxy</span><span class="params">()</span>:</span></span><br><span class="line">    <span class="comment"># cond.acquire()跟cond.release()，可以实现对一段命令的加解锁（Lock）</span></span><br><span class="line">    <span class="comment"># 就如同上厕所一样，一个任务执行到加锁的一段，如果另一个任务也执行到这一段，就会暂停挂起，等待排队</span></span><br><span class="line">    <span class="comment"># proxies跟proxies_used是每个任务共享的全局变量（Global Variable），对于共享变量的操作，是要加锁的</span></span><br><span class="line">    <span class="comment"># 如果代理就剩一个，然后两个任务都跑到这一段，那就出事了= =</span></span><br><span class="line">    <span class="keyword">await</span> cond.acquire()</span><br><span class="line">    proxy = <span class="string">''</span></span><br><span class="line">    <span class="keyword">try</span>:</span><br><span class="line">        <span class="comment"># 等待代理分配器通知= =</span></span><br><span class="line">        <span class="comment"># 代理分配器会在有可用代理，或者代理全部凉凉的时候唤醒这些等待者</span></span><br><span class="line">        <span class="keyword">await</span> cond.wait()</span><br><span class="line">        <span class="comment"># 如果有可用代理，就挑一个，没有就直接返回空字符串</span></span><br><span class="line">        <span class="comment"># 可以看上面的crawl_movie_url任务，直接凉凉= =</span></span><br><span class="line">        <span class="keyword">if</span> len(proxies) &gt; <span class="number">0</span>:</span><br><span class="line">            <span class="comment"># 从代理队列头部取出一个代理</span></span><br><span class="line">            proxy = proxies.popleft()</span><br><span class="line">            <span class="comment"># 把这个代理加到正在使用的代理集合中</span></span><br><span class="line">            proxies_used.add(proxy)</span><br><span class="line">    <span class="keyword">finally</span>:</span><br><span class="line">        cond.release()</span><br><span class="line">    <span class="keyword">return</span> proxy</span><br></pre></td></tr></table></figure>
<p>面对这群嗷嗷待哺的任务们，我们的代理服务器分配任务<code>allocate_proxy</code>，就可以这样设计了</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">async</span> <span class="function"><span class="keyword">def</span> <span class="title">allocate_proxy</span><span class="params">(max_tasks)</span>:</span></span><br><span class="line">    <span class="comment"># 代理分配任务，本身就相当于一个服务，因此这里采用循环的方式来设计</span></span><br><span class="line">    <span class="keyword">while</span> <span class="literal">True</span>:</span><br><span class="line">        <span class="comment"># 上锁，劳资要给别的任务分配代理了</span></span><br><span class="line">        <span class="comment"># 而且还得看代理队列呢，其他任务先别着急= =</span></span><br><span class="line">        <span class="keyword">await</span> cond.acquire()</span><br><span class="line">        will_break = <span class="literal">False</span>  <span class="comment"># 是否退出代理分配任务</span></span><br><span class="line">        will_delay = <span class="literal">False</span>  <span class="comment"># 下一个循环是否要延迟长一点</span></span><br><span class="line">        <span class="keyword">try</span>:</span><br><span class="line">            <span class="keyword">if</span> task_count == max_tasks:</span><br><span class="line">                <span class="comment"># task_count指当前完成的爬虫任务数</span></span><br><span class="line">                <span class="comment"># 如果到了最大值，说明全部任务都结束了</span></span><br><span class="line">                <span class="comment"># 这个时候代理分配任务也就完成任务了</span></span><br><span class="line">                will_break = <span class="literal">True</span></span><br><span class="line">            <span class="comment"># 看代理队列还有木有可用的</span></span><br><span class="line">            len_proxies = len(proxies)</span><br><span class="line">            <span class="keyword">if</span> len_proxies == <span class="number">0</span>:</span><br><span class="line">                <span class="keyword">if</span> len(proxies_used) == <span class="number">0</span>:</span><br><span class="line">                    <span class="comment"># 代理队列没代理，连tm正在用的代理也是空的，岂不是凉凉= =</span></span><br><span class="line">                    <span class="comment"># 把这个可怕的信息告诉给所有任务吧= =然后劳资也跑路= =</span></span><br><span class="line">                    cond.notify_all()</span><br><span class="line">                    will_break = <span class="literal">True</span></span><br><span class="line">                <span class="keyword">else</span>:</span><br><span class="line">                    <span class="comment"># 代理都在用着呢，等多一会儿再给大家分配吧= =</span></span><br><span class="line">                    will_delay = <span class="literal">True</span></span><br><span class="line">            <span class="keyword">else</span>:</span><br><span class="line">                <span class="comment"># 代理队列有多少代理，最多通知多少个任务去拿代理去</span></span><br><span class="line">                cond.notify(len_proxies)</span><br><span class="line">        <span class="keyword">finally</span>:</span><br><span class="line">            cond.release()</span><br><span class="line">            <span class="keyword">if</span> will_break:</span><br><span class="line">                <span class="keyword">break</span></span><br><span class="line">            <span class="keyword">elif</span> will_delay:</span><br><span class="line">                <span class="comment"># 歇多几秒，再分配代理给其它嗷嗷待哺的任务</span></span><br><span class="line">                <span class="comment"># 相当于爬虫访问网页的时间间隔设置</span></span><br><span class="line">                <span class="comment"># 豆瓣白天2s左右晚上3~4s左右差不多</span></span><br><span class="line">                <span class="keyword">await</span> asyncio.sleep(get_proxy_delay_time())</span><br><span class="line">            <span class="keyword">else</span>:</span><br><span class="line">                <span class="comment"># 歇一丢丢时间，把自己排在任务调度后面</span></span><br><span class="line">                <span class="comment"># 不然while True死循环，别的任务就跑不了了</span></span><br><span class="line">                <span class="keyword">await</span> asyncio.sleep(proxy_search_period)</span><br></pre></td></tr></table></figure>
<h2 id="爬虫主任务"><a href="#爬虫主任务" class="headerlink" title="爬虫主任务"></a>爬虫主任务</h2><p>有了代理分配这个强劲的后盾，我们的爬虫任务就可以顺利进行啦！</p>
<p>免费的代理好多都没法用的，需要在爬虫的过程中不断舍弃。废话不多说，直接上代码！</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br><span class="line">46</span><br><span class="line">47</span><br><span class="line">48</span><br><span class="line">49</span><br><span class="line">50</span><br><span class="line">51</span><br><span class="line">52</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">async</span> <span class="function"><span class="keyword">def</span> <span class="title">crawl_movie_url</span><span class="params">(session, url, movie_num)</span>:</span></span><br><span class="line">    <span class="keyword">while</span> <span class="literal">True</span>:</span><br><span class="line">        <span class="comment"># 这段上面讲了= =</span></span><br><span class="line">        proxy = <span class="keyword">await</span> get_proxy()</span><br><span class="line">        <span class="keyword">if</span> <span class="keyword">not</span> proxy:</span><br><span class="line">            log(movie_num, <span class="string">'TMD代理全部挂了，凉凉= ='</span>)</span><br><span class="line">            <span class="keyword">return</span></span><br><span class="line">        <span class="comment"># result存储爬取的数据，log函数打印日志（得自定义实现= =）</span></span><br><span class="line">        result = &#123;<span class="string">'number'</span>: movie_num, <span class="string">'url'</span>: url, <span class="string">'proxy'</span>: proxy&#125;</span><br><span class="line">        log(movie_num, <span class="string">'代理%s正在访问%s...'</span> % (proxy, url))</span><br><span class="line">        success = <span class="literal">True</span>  <span class="comment"># 是否爬取成功的标志</span></span><br><span class="line">        <span class="keyword">try</span>:</span><br><span class="line">            <span class="comment"># 用get获取数据，判断状态码，而后解析数据</span></span><br><span class="line">            response = <span class="keyword">await</span> session.get(url, proxy=proxy, headers=headers, timeout=proxy_connection_timeout)</span><br><span class="line">            status_code = response.status</span><br><span class="line">            <span class="keyword">if</span> status_code == <span class="number">200</span>:</span><br><span class="line">                html = <span class="keyword">await</span> response.text()</span><br><span class="line">                soup = BeautifulSoup(html, html_parser)</span><br><span class="line">                <span class="keyword">for</span> k <span class="keyword">in</span> content_func_map.keys():</span><br><span class="line">                    <span class="keyword">try</span>:</span><br><span class="line">                        <span class="comment"># 按最开始设的爬取规则抓数据，存到result里</span></span><br><span class="line">                        content = content_func_map[k](soup)</span><br><span class="line">                        result[k] = content</span><br><span class="line">                    <span class="keyword">except</span> Exception <span class="keyword">as</span> e:</span><br><span class="line">                        <span class="comment"># 如果爬不了，很有可能get到的网页变了！</span></span><br><span class="line">                        <span class="comment"># 比如叫你登录啥啥的，这说明代理被豆瓣临时小黑屋了，果断放弃这个代理</span></span><br><span class="line">                        log(movie_num, <span class="string">'代理%s爬取%s信息失败！果断放弃掉！错误信息：%s\n'</span> % (proxy, k, e))</span><br><span class="line">                        success = <span class="literal">False</span></span><br><span class="line">                        <span class="keyword">break</span></span><br><span class="line">            <span class="keyword">else</span>:</span><br><span class="line">                   <span class="comment"># 如果状态码不对，很有可能是400啥的，说明也被豆瓣小黑屋了，果断放弃掉这个代理</span></span><br><span class="line">                log(movie_num, <span class="string">'代理%s获取数据失败！果断放弃掉！状态码: %d！'</span> % (proxy, status_code))</span><br><span class="line">                success = <span class="literal">False</span></span><br><span class="line">        <span class="keyword">except</span> Exception <span class="keyword">as</span> e:</span><br><span class="line">            <span class="comment"># 代理链接或者代理发送请求都有问题，果断不要了</span></span><br><span class="line">            log(movie_num, <span class="string">'代理%s连接出错，果断放弃掉！！！错误信息：%s！'</span> % (proxy, e))</span><br><span class="line">            success = <span class="literal">False</span></span><br><span class="line">        <span class="keyword">finally</span>:</span><br><span class="line">            <span class="keyword">if</span> success:</span><br><span class="line">                <span class="comment"># 成功爬取数据，把爬取结果加上，把任务完成数加上</span></span><br><span class="line">                <span class="keyword">global</span> results</span><br><span class="line">                <span class="keyword">global</span> task_count</span><br><span class="line">                results.append(result)</span><br><span class="line">                task_count = task_count + <span class="number">1</span></span><br><span class="line">                log(movie_num, <span class="string">'当前爬到信息的电影数: %d，爬到信息：%s'</span> % (task_count, str(result)))</span><br><span class="line">                <span class="comment"># 这个代理还能用，给力！proxies_used里删掉它</span></span><br><span class="line">                <span class="comment"># 然后把它放到proxies的尾部（append）</span></span><br><span class="line">                <span class="keyword">await</span> recycle_proxy(proxy)</span><br><span class="line">                <span class="keyword">break</span></span><br><span class="line">            <span class="keyword">else</span>:</span><br><span class="line">                <span class="comment"># 这个代理不给力，直接从proxies_used删掉吧~</span></span><br><span class="line">                <span class="keyword">await</span> remove_proxy(proxy)</span><br></pre></td></tr></table></figure>
<p>试试看吧~</p>
<h2 id="总结"><a href="#总结" class="headerlink" title="总结"></a>总结</h2><p>豆瓣Top 250爬虫，其实更多的难点，在于如何组织、调度你的资源，更有效率地处理数据。爬虫的工具、软件，其实都已经烂大街</p>
<p>对于软件，集搜客、八爪鱼之类的就能完成需求</p>
<p>对于代理池，github上就有许多项目可以clone下来去获得</p>
<p>对于爬虫框架，其实可以踩踩<code>scrapy</code>库的坑，这是一个非常成熟的爬虫框架</p>
<p>对于获取异步加载（不是当即就在response里，而是后面才加载到）的数据，可以使用<span class="exturl" data-url="aHR0cDovL3BoYW50b21qcy5vcmcv" title="http://phantomjs.org/">PhantomJS<i class="fa fa-external-link"></i></span>一类的工具，或者利用Chrome开发者工具，采用抓包+模拟HTTP请求的方式，获取相应数据。</p>
<p>最后介绍一个大杀器——<span class="exturl" data-url="aHR0cHM6Ly9zZWxlbml1bS1weXRob24ucmVhZHRoZWRvY3MuaW8v" title="https://selenium-python.readthedocs.io/">Selenium<i class="fa fa-external-link"></i></span>，作为一款浏览器测试驱动，selenium甚至可以模拟浏览器操作，百试不爽，谁用谁知道！</p>

      
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                  var upperBound = parseInt('5');
                  if (upperBound >= 0) {
                    slicesOfContent = slicesOfContent.slice(0, upperBound);
                  }

                  // highlight title and content

                  function highlightKeyword(text, slice) {
                    var result = '';
                    var prevEnd = slice.start;
                    slice.hits.forEach(function (hit) {
                      result += text.substring(prevEnd, hit.position);
                      var end = hit.position + hit.length;
                      result += '<b class="search-keyword">' + text.substring(hit.position, end) + '</b>';
                      prevEnd = end;
                    });
                    result += text.substring(prevEnd, slice.end);
                    return result;
                  }

                  var resultItem = '';

                  if (slicesOfTitle.length != 0) {
                    resultItem += "<li><a href='" + articleUrl + "' class='search-result-title'>" + highlightKeyword(title, slicesOfTitle[0]) + "</a>";
                  } else {
                    resultItem += "<li><a href='" + articleUrl + "' class='search-result-title'>" + title + "</a>";
                  }

                  slicesOfContent.forEach(function (slice) {
                    resultItem += "<a href='" + articleUrl + "'>" +
                      "<p class=\"search-result\">" + highlightKeyword(content, slice) +
                      "...</p>" + "</a>";
                  });

                  resultItem += "</li>";
                  resultItems.push({
                    item: resultItem,
                    searchTextCount: searchTextCount,
                    hitCount: hitCount,
                    id: resultItems.length
                  });
                }
              })
            };
            if (keywords.length === 1 && keywords[0] === "") {
              resultContent.innerHTML = '<div id="no-result"><i class="fa fa-search fa-5x"></i></div>'
            } else if (resultItems.length === 0) {
              resultContent.innerHTML = '<div id="no-result"><i class="fa fa-frown-o fa-5x"></i></div>'
            } else {
              resultItems.sort(function (resultLeft, resultRight) {
                if (resultLeft.searchTextCount !== resultRight.searchTextCount) {
                  return resultRight.searchTextCount - resultLeft.searchTextCount;
                } else if (resultLeft.hitCount !== resultRight.hitCount) {
                  return resultRight.hitCount - resultLeft.hitCount;
                } else {
                  return resultRight.id - resultLeft.id;
                }
              });
              var searchResultList = '<ul class=\"search-result-list\">';
              resultItems.forEach(function (result) {
                searchResultList += result.item;
              })
              searchResultList += "</ul>";
              resultContent.innerHTML = searchResultList;
            }
          }

          if ('auto' === 'manual') {
            input.addEventListener('input', inputEventFunction);
          } else {
            $('.search-icon').click(inputEventFunction);
            input.addEventListener('keypress', function (event) {
              if (event.keyCode === 13) {
                inputEventFunction();
              }
            });
          }

          // remove loading animation
          $(".local-search-pop-overlay").remove();
          $('body').css('overflow', '');

          proceedsearch();
        }
      });
    }

    // handle and trigger popup window;
    $('.popup-trigger').click(function(e) {
      e.stopPropagation();
      if (isfetched === false) {
        searchFunc(path, 'local-search-input', 'local-search-result');
      } else {
        proceedsearch();
      };
    });

    $('.popup-btn-close').click(onPopupClose);
    $('.popup').click(function(e){
      e.stopPropagation();
    });
    $(document).on('keyup', function (event) {
      var shouldDismissSearchPopup = event.which === 27 &&
        $('.search-popup').is(':visible');
      if (shouldDismissSearchPopup) {
        onPopupClose();
      }
    });
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      mermaid.initialize({
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    var $wrap = $('<div>').addClass('highlight-wrap');
    $(e).after($wrap);
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